Machine Learning Engineer --Full-time (H1B/OPT Accepted)

Overview

Remote
On Site
USD 40-50
Full Time
Part Time
Accepts corp to corp applications
Contract - Independent
Contract - W2

Skills

Artificial Intelligence
Scalability
Debugging
Algorithms
TensorFlow
PyTorch
scikit-learn
Evaluation
Programming Languages
Python
R
Java
Big Data
Apache Hadoop
Apache Spark
Cloud Computing
Amazon Web Services
Microsoft Azure
Google Cloud Platform
Google Cloud
Version Control
Git
Continuous Integration
Continuous Delivery
Problem Solving
Conflict Resolution
Analytical Skill
Communication
Collaboration
Deep Learning
Natural Language Processing
Computer Vision
Machine Learning (ML)
Data Science

Job Details

Job Title: Machine Learning Engineer - W2 (H1B/OPT) Accepted

Location: Dallas, TX (Remote)

Duration: Long Term

Experience: 6-10 Years



We're searching for a skilled Machine Learning Engineer to design, develop, and deploy machine learning models that drive our data-driven solutions. You'll collaborate with data scientists, software engineers, and product managers to bring innovative AI solutions to life.

Responsibilities:

  • Design, develop, and implement machine learning models and algorithms.
  • Preprocess and analyze large datasets to extract meaningful features.
  • Train, test, and validate machine learning models to ensure accuracy and efficiency.
  • Deploy machine learning models into production environments and monitor their performance.
  • Work closely with data scientists and product managers to understand requirements and translate them into technical solutions.
  • Optimize models for performance, scalability, and reliability.
  • Conduct code reviews and contribute to a collaborative development environment.
  • Troubleshoot and debug complex technical issues related to machine learning models.
  • Stay up-to-date on the latest advancements in machine learning and related technologies.

Qualifications:

  • 5+ years of experience as a Machine Learning Engineer.
  • In-depth knowledge of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Experience with data preprocessing, feature engineering, and model evaluation.
  • Proficiency in programming languages such as Python, R, or Java.
  • Experience with big data technologies (e.g., Hadoop, Spark) is a plus.
  • Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine learning services.
  • Proficiency in version control systems (Git) and familiarity with CI/CD pipelines.
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration skills.
  • Experience with deep learning, natural language processing, or computer vision is a plus.
  • Relevant certifications in machine learning or data science are a plus.

We look forward to meeting you!

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